Cyber–Physical Co-regulation and Optimization Methods in Smart Power Systems from the Perspective of Cyber–Physical Symmetry

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 4000

Special Issue Editors


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Associate Professor, Institute of Advanced Technology, Nanjing University of Post and Telecommunications, Nanjing 210003, China
Interests: active distribution network and microgrid

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Guest Editor
Department of Electrical Engineerting, Tsinghua University, Beijing 100084, China
Interests: cyber-physical system; demand response; wireless communication; resource allocation

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Guest Editor
College of Computer Science, South-Central Minzu University, Wuhan 430074, China
Interests: resource allocation in wireless communication systems

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Guest Editor
Institute of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
Interests: localization and optimization

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Guest Editor
Associate Professor, School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Interests: smart grid; vehicle-to-grid; vehicular networks
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Special Issue Information

Dear Colleagues,

With the large-scale integration of new energy resources into the grid, power system resource regulation has become a key technology in facilitating the consumption of distributed renewable energy and supporting the realization of the carbon neutrality goals. However, as the proportion of distributed energy resources and flexible loads in the grid gradually increases, their disordered disturbance characteristics cause frequent problems such as the deterioration of power quality and over-limit flow. Due to a lack of active supporting technology for source–network–load–storage resource management, power system security and high-quality and economic operation face huge challenges. To fully "wake up" the regulation ability of controllable resources in the system, it is urgent to apply advanced communication technologies and regulation technologies to the power system so as to enhance the overall viewability and controllability of the system, and make the power system operation more intelligent. However, with the continuous increase in new energy proportion and the gradual deepening of cyber–physical fusion in the systems, it not only intensifies the uncertainty of source-side output and load-side demand in the physical layer but also makes the information uncertainties such as transmission delay, packet loss, and network attacks more prominent. In addition, the two kinds of uncertainties are symmetry and superimposition, which are prone to present the feature of “1 + 1 > 2”, seriously affecting the operation safety, quality and economy of new cyber–physical power systems. Therefore, based on the perspective of information and physical symmetry, it is urgent to explore and study the cyber–physical co-regulation and optimization methods in smart power systems so as to improve the performance of the systems under multiple uncertainties.

Dr. Bo Zhang
Dr. Pei Liu
Dr. Yuanai Xie
Dr. Haiyan Zhao
Dr. Weifeng Zhong
Guest Editors

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Keywords

  • application of emerging technologies (e.g., federated learning, digital twin, blockchain, metaverse, AIGC, and B5G) in power systems
  • collaborative optimization of energy information resources for cyber–physical convergence of smart power systems
  • cyber–physical–social coupling system technology for smart power systems
  • smart power emergency communication system based on space–air–ground integration
  • attack detection and defense cyber–physical smart power systems
  • key technology for panoramic situation awareness of smart power systems
  • key technology for secure and efficient data transmission in smart power systems
  • key technology for safe/high-quality/economic operation and control of cyber–physical smart power systems
  • key technology for fault location and recovery of smart power systems under extreme disasters
  • key technology of cyber–physical cooperative defense for endogenous security problems of smart power systems
  • key technology of data privacy protection and trusted encryption for smart power systems

Published Papers (3 papers)

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Research

22 pages, 3961 KiB  
Article
An Equivalent-Perceptional Intertemporal Choice Heuristics Model for Electric Operation Vehicle Charging Behavior
by Yue Han, Yi Quan, Peiwen Li, Bo Fu, Mei Xie and Haiyan Zhao
Symmetry 2024, 16(3), 374; https://doi.org/10.3390/sym16030374 - 20 Mar 2024
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Abstract
The inherent stochasticity of electric operation vehicle (EOV) charging poses challenges to the stability and efficiency of regional power distribution networks. Existing charging behavior decision-making models often prioritize revenue considerations, neglecting the influence of multi-time-span characteristics and the potential irrationality of EOV owners. [...] Read more.
The inherent stochasticity of electric operation vehicle (EOV) charging poses challenges to the stability and efficiency of regional power distribution networks. Existing charging behavior decision-making models often prioritize revenue considerations, neglecting the influence of multi-time-span characteristics and the potential irrationality of EOV owners. To address these limitations, this study proposes a comprehensive framework encompassing three aspects. First, operational data are statistically analyzed to reconstruct EOV operation scenarios, establishing a dynamic charging scheme tailored to multi-time-span characteristics. Second, an improved ITCH model is developed using operational equivalent change to incorporate both gains and losses. Third, a WFL framework is employed to integrate the perceptual attenuation of revenue into the ITCH model. Simulation results show that decision-makers (DMs) demonstrate a preference for charging schemes with high equivalent perceived revenues and low time costs. Moreover, when the charging price is doubled, revenue perception attenuation leads decision-makers to postpone their charging behavior. Compared to other models, the equivalent perception intertemporal choice heuristics (EP-ITCH) charging model results in reduced load peaks, valleys, and variances on the grid side. This study highlights the model’s effectiveness and accuracy in optimizing EOV charging infrastructure. Full article
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22 pages, 1870 KiB  
Article
Attack–Defense Confrontation Analysis and Optimal Defense Strategy Selection Using Hybrid Game Theoretic Methods
by Bao Jin, Xiaodong Zhao and Dongmei Yuan
Symmetry 2024, 16(2), 156; https://doi.org/10.3390/sym16020156 - 29 Jan 2024
Viewed by 736
Abstract
False data injection attacks are executed in the electricity markets of smart grid systems for financial benefits. The attackers can maximize their profits through modifying the estimated transmission power and changing the prices of market electricity. As a response, defenders need to minimize [...] Read more.
False data injection attacks are executed in the electricity markets of smart grid systems for financial benefits. The attackers can maximize their profits through modifying the estimated transmission power and changing the prices of market electricity. As a response, defenders need to minimize expected load losses and generator trips through load and power generation adjustments. The selection of strategies of the attacking and defending sides turns out to be a symmetric game process. This article proposes a hybrid game theory method for analyzing the attack–defense confrontation: firstly, a micro-grid-based power market model considering false data injection attacks is established using the Nash equilibrium method; secondly, the attack–defense game function is constructed and solved via the Stackelberg equilibrium algorithm. The Markov game algorithm and distributed learning algorithm are used to update equilibrium function; finally, a dynamic game behavior model of the two players is constructed through simulating the attack–defense probability. The evolutionary game method is used to select the optimal defense strategy for dynamic probability changes. Modified IEEE standard bus systems are illustrated to certify the effectiveness of the proposed model. Full article
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20 pages, 4024 KiB  
Article
A Novel Detection and Identification Mechanism for Malicious Injection Attacks in Power Systems
by Hongfeng Zhang, Xinyu Wang, Lan Ban and Molin Sun
Symmetry 2023, 15(12), 2104; https://doi.org/10.3390/sym15122104 - 23 Nov 2023
Viewed by 661
Abstract
The integration of advanced sensor technology and control technology has gradually improved the operational efficiency of traditional power systems. Due to the undetectability of these attacks using traditional chi-square detection techniques, the state estimation of power systems is vulnerable to cyber–physical attacks, For [...] Read more.
The integration of advanced sensor technology and control technology has gradually improved the operational efficiency of traditional power systems. Due to the undetectability of these attacks using traditional chi-square detection techniques, the state estimation of power systems is vulnerable to cyber–physical attacks, For this reason, this paper presents a novel detection and identification framework for detecting malicious attacks in power systems from the perspective of cyber–physical symmetry. To consider the undetectability of cyber–physical attacks, a physical dynamics detection model using the unknown input observers (UIOs) and cosine similarity theorem is proposed. Through the design of UIO parameters, the influence of attacks on state estimation can be eliminated. A cosine similarity value-based detection criterion is proposed to replace the traditional detection threshold. To further cut down the effects caused by malicious attacks, an observer combination-based attack identification framework is established. Finally, simulations are given to demonstrate that the proposed security method can detect and identify the injected malicious attacks quickly and effectively. Full article
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